TY - JOUR
T1 - Automatic quantification of muscle volumes in magnetic resonance imaging scans of the lower extremities
AU - Brunner, Gerd
AU - Nambi, Vijay
AU - Yang, Eric
AU - Kumar, Anirudh
AU - Virani, Salim S.
AU - Kougias, Panagiotis
AU - Shah, Dipan
AU - Lumsden, Alan
AU - Ballantyne, Christie M.
AU - Morrisett, Joel D.
N1 - Funding Information:
This work was supported in part by National Institutes of Health grants T32HL07812 , R01HL63090 , and R01HL075824 . The authors wish to express their thanks to Alaina Yawn and Lee Sanford for assistance in image acquisition.
PY - 2011/10
Y1 - 2011/10
N2 - Muscle volume measurements are essential for an array of diseases ranging from peripheral arterial disease, muscular dystrophies, neurological conditions to sport injuries and aging. In the clinical setting, muscle volume is not routinely measured due to the lack of standardized ways for its repeatable quantification. In this paper, we present magnetic resonance muscle quantification (MRMQ), a method for the automatic quantification of thigh muscle volume in magnetic resonance imaging (MRI) scans. MRMQ integrates a thigh segmentation and nonuniform image gradient correction step, followed by feature extraction and classification. The classification step leverages prior probabilities, introducing prior knowledge to a maximum a posteriori classifier. MRMQ was validated on 344 slices taken from 60 MRI scans. Experiments for the fully automatic detection of muscle volume in MRI scans demonstrated an averaged accuracy, sensitivity and specificity for leave-one-out cross-validation of 88.3%, 93.6% and 87.2%, respectively.
AB - Muscle volume measurements are essential for an array of diseases ranging from peripheral arterial disease, muscular dystrophies, neurological conditions to sport injuries and aging. In the clinical setting, muscle volume is not routinely measured due to the lack of standardized ways for its repeatable quantification. In this paper, we present magnetic resonance muscle quantification (MRMQ), a method for the automatic quantification of thigh muscle volume in magnetic resonance imaging (MRI) scans. MRMQ integrates a thigh segmentation and nonuniform image gradient correction step, followed by feature extraction and classification. The classification step leverages prior probabilities, introducing prior knowledge to a maximum a posteriori classifier. MRMQ was validated on 344 slices taken from 60 MRI scans. Experiments for the fully automatic detection of muscle volume in MRI scans demonstrated an averaged accuracy, sensitivity and specificity for leave-one-out cross-validation of 88.3%, 93.6% and 87.2%, respectively.
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U2 - 10.1016/j.mri.2011.02.033
DO - 10.1016/j.mri.2011.02.033
M3 - Article
C2 - 21855242
AN - SCOPUS:80052638028
SN - 0730-725X
VL - 29
SP - 1065
EP - 1075
JO - Magnetic Resonance Imaging
JF - Magnetic Resonance Imaging
IS - 8
ER -